How Does Technology Affect Which Men Women Choose?

In previous posts:

I attempted to outline an answer to the question, “Why does it appear that the vast majority of women prefer the same small group of men?”

I began by wondering if a simple statistical model, simulated in NetLogo, could qualitatively produce the same distribution found “on every dating site…Tinder,, DateHookup (as per the figure above)”. In my model, I decided to test how simple mate selection strategies resulted in wildly different statistical distributions in each of the final selection pools.

In the simulation, men make their mate selection decisions by minimizing over the age of their prospective partners, whereas women maximize over the status of the men in their accessible vicinity. Could it be that just two simplifying assumptions are enough to replicate real world data, even if only qualitatively at first? Following Solow’s Law of Simplicity, which states the the results of a model should not be very sensitive to its simplifying assumptions, I pressed forward.

If one were naive and simply assumed that men and women preferred within each other a balanced distribution of personality and other socioeconomic qualities, then the world really ought to look a lot more like the first two of four computed simulations above. But it doesn’t. Although the simulation results above show only the most extreme scenarios, one biased in the direction of the median man (Regulated Monogamy, or Patriarchy) and the other in the direction of the median female (Open Hypergamy), it is interesting to note that contemporary real world data looks a lot more like the extreme scenario on the female side of spectrum.

In summation, I found the following:

  • There is a strong outcome asymmetry in preferences between men and women when it comes to selecting a mate, i.e. women prefer the same small group of men; men are indifferent to the vast majority of women.
  • I use “indifference” above in the technical economic sense, i.e. the rate of substitution of a good at which there is no change in utility. In this sense, male demand for women has a significantly more positive cross elasticity of demand than female demand for men.
  • Roughly translated, women are more “substitutable” to men than men are to women, i.e. women lose more when they lose access to a valuable man than the reverse.
  • Said another way, women desire high status men far more than men desire high status women.
  • What follows is that when women are free to have many partners over the course of a lifetime, sex and mating inequality becomes high; asymmetry in intersexual selection ensures that the same is not true if such were the same for men.
  • The positional trait (social status in this case), when amplified by both technology and the freedom to use those technologies, i.e. social norms favoring the Feminine Imperative (in Saudi Barbaria, women wear burkas and can’t use Tinder) the selection pool of prospective mates increases far faster for the median woman than it does for median man.
  • Given that women are primarily interested in status, which is a positional good, then any technology that amplifies a woman’s ability to be noticed by high status men, will also increase mating inequality. Consider, for example, how men do not benefit nearly as much from the scale offered by Tinder as do women. 100 swipes will get you 1 date if you are a man, and where it only takes 1 if you are a woman.
  • In the graphs shown below, Hypergamy is calculated as the difference in median in-degree (number of incoming links) between the two distributions.
  • Age in men tends to be a proxy of social status, where as age in women tends to determine genetic quality. Genetic quality is normally distributed, on a Bell Curve, whereas social status (and the wealth and income that results) is either log-normally or Pareto distributed in a population (What if Bill Gates Were as Tall as His Money?), following the truism that “20% of the men get 80% of the women.” While close to true, what my simulations actually show is that what is really happening is something closer to “20% of the men receive 80% of all female intent.”
  • Hypergamy, then, is ever present. The only thing that changes whether it is realized or not is the extent to which women are free to act on it. Hypergamy doesn’t necessarily guarantee an inequality in actual sexual encounters, but the more free that women are to act on it (and this is personal speculation) the more likely are there to be social norms and institutions favoring women, i.e. fault-free divorce, preferential child custody laws, anti-slut shaming, hyper-popularity on social media, (the free trips to Dubai that entails), etc.
  • A final, somewhat counter-intuitive point. An increase in the female-to-male population sex ratio increases competition for women amongst men because it increases the time until which women decide they are ready to “settle” for inferior quality mates (Briffault’s Law tells us that the female, not the male, determines all the conditions of the animal family, and so when there are more opportunities to do better, why settle early?). As a result, and at least in the context of my simulations, there is a sub-linear scaling law in which a doubling of the population of women compared to men increases the median woman’s number of matches by 50%. I’m not sure what this would look like in real life, but when I was in high school, a party with a “good ratio” was all any guy talked about. That ratio is probably a lot closer to parity than most believe. Unless you’re a member of Cad Club, you probably don’t want to invite more girls to your party.

At this point, I would like to speculate far beyond the scope of my initial simulations. Hypergamy, I believe, as an evolutionary mechanism, is likely not restricted to dating markets alone. Successful genetic algorithms for manufacturing the ideal “kitchen sink faucet” (see Genetic Algorithms in Industrial Design), for example, could likely benefit from a system that maximizes Hypergamy. In summation, Hypergamy is a general purpose filtering mechanism for maximizing the genetic quality of a stock of evolving agents.

In simple systems with few additional feedback loops, Hypergamy can be a good thing. In complex systems, such as human societies, however, Hypergamy, the mating access and genetic inequality that results, is likely to cause a society to self-implode, in much the same way that too unequal a distribution of household income in an economy, for example, stalls growth by making it impossible for a debt-loaded Middle Class to continue consuming increasingly sophisticated and expensive technology. My next few posts will cover this explicitly. The Mating Economy is likely best understood as a series of feedback loops, in which a balance between Regulated Monogamy and Open Hypergamy maximizes the “socioeconomic growth rate” of a Civilization.

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